3 papers
cs.CV2026
Deep Auxiliary Learning via Bilevel Feature Optimization for Label-Efficient Medical Image Segmentation
Fuping Wu, Xi Jia, Le Zhang +4
Auxiliary learning (AL), which can improve the performance of a primary task by leveraging related auxiliary tasks, is commonly regarded as a special case of multi-task learning. E…
cs.CV2025
Emerging Semantic Segmentation from Positive and Negative Coarse Label Learning
Le Zhang, Fuping Wu, Arun Thirunavukarasu +3
Large annotated datasets are vital for training segmentation models, but pixel-level labeling is time-consuming, error-prone, and often requires scarce expert annotators, especiall…
cs.CV2023
Multi-Task Cooperative Learning via Searching for Flat Minima
Fuping Wu, Le Zhang, Yang Sun +3
Multi-task learning (MTL) has shown great potential in medical image analysis, improving the generalizability of the learned features and the performance in individual tasks. Howev…